Version: 1.0
Last Updated: February 2026
Scenario: Migrating a Kafka deployment from a source Kubernetes cluster to a target cluster using application-level replication, with ArgoCD managing both sides.
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| #!/usr/bin/env bash | |
| # Minimal test: Claude Opus 4.6 via Vertex AI on GCP | |
| set -euo pipefail | |
| PROJECT=$(gcloud config get-value project 2>/dev/null) | |
| LOCATION="us-east5" | |
| MODEL="claude-opus-4-6@default" | |
| TOKEN=$(gcloud auth print-access-token) | |
| API_URL="https://${LOCATION}-aiplatform.googleapis.com/v1/projects/${PROJECT}/locations/${LOCATION}/publishers/anthropic/models/${MODEL}:rawPredict" |
Create a reusable Claude skill that discovers important pages in web applications, captures screenshots before/after code changes, and generates visual comparison reports. Works in headless environments and requires zero modifications to target applications.
The skill will support three main commands:
/screenshot discover- Analyze codebase to find main pages/routes
Audit Date: January 28, 2026 Organization: konveyor
This audit analyzed GitHub labels across the Konveyor organization to identify inconsistencies, redundancies, and opportunities for standardization. The findings reveal significant label fragmentation that can be addressed through a structured consolidation strategy based on open source best practices.
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